Land surface temperature (LST) is an important parameter that affects the water cycle, environmental changes, and energy balance at global and regional scales. Herein, a time series analysis was conducted to estimate the monthly, seasonal, and interannual variations in LST during 2001–2019 in the Tarim Basin, China. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) LST, air temperature, air pressure, relative humidity, wind speed, precipitation, elevation, and land-cover type data, we analyzed the spatio-temporal change characteristics of LST and the influencing factors. High LSTs occurred in the desert and plains and low LSTs occurred in surrounding mountain regions. The highest LST was recorded in July (25.1 °C) and the lowest was in January (−9.5 °C). On a seasonal scale, LST decreased in the order: summer > spring > autumn > winter. Annual LST showed an increasing trend of 0.2 °C/10 a in the desert and mountain areas, while the plains indicated a decreasing trend. In spring and autumn, western regions were dominated by a downward trend, whereas in winter a downward trend occurred in eastern regions. In summer, areas covered by vegetation were dominated by a downward trend, and desert and bare lands were dominated by an upward trend. Random forest (RF) model analysis showed that elevation was the most significant influencing factor (22.1%), followed by mean air temperature (20.1%). Correlation analysis showed that the main climatic factors air temperature, relative humidity, and elevation have a good correlation with the LST. Land-cover type also affected LST; during February–December the lowest LST was observed for permanent glacier snow and the highest was observed in the desert. El Nino and La Nina greatly influenced the LST variations. The North Atlantic Oscillation and Pacific Decadal Oscillation indices were consistent with the mean LST anomaly, indicating their considerable influence on LST variations.

Recently, climate change has attracted many researchers worldwide, among which the analysis of different levels of precipitation changes is essential. In this study, we analyzed the spatial and temporal variations in the precipitation amount, precipitation days, precipitation intensity, and contribution rates in the Tarim Basin (TB) from 1961–2019. Our results demonstrate that the annual mean rainstorm, trace amounts of snow, and light snow exhibit downward trends, while all the other precipitation types increase. Both rainfall and snowfall were mainly concentrated in the western mountainous region. Rainstorms in the eastern parts of the TB were significantly higher than those in the western parts. Heavy rainstorm intensity is mainly concentrated on the southern slope of the Tianshan Mountains. The spatial distribution of trace amounts of snow, light snow, and moderate snow intensities has no prominent regional distribution characteristics. Heavy snow is mainly concentrated in the northern parts of the TB, whereas snowstorms are mainly concentrated in the western parts of the TB. Heavy snowstorms occur at a few stations in western mountainous areas. The relative contribution to total precipitation is the largest for rainfall, the second largest for snowfall, and the smallest for rain and snow. In the TB, the contribution of light rain/light drizzle to the total rainfall is the largest or smallest at 42-71 %/0.8-2.2 %. The contribution of light snow/trace amounts of snow to the total snowfall is the higest and lowest between 28.74~71.95 % and 1.60~13.61 %.

Drought presents significant challenges in arid regions, adversely impacting agriculture, water resources, and ecosystems. In Xinjiang, Northwest China, although large-scale climatic phenomena are well studied, finer-scale climatic variability in subregions such as the Ili River Valley (IRV) remains understudied. This knowledge gap impairs effective agricultural planning and environmental management in this ecologically fragile but agriculturally important region. In this study, we analyze the spatiotemporal evolution of drought in the IRV from 1961 to 2023, using data from ten meteorological stations. We applied the SPEI drought Index alongside Sen's trend analysis, the Mann-Kendall test, the cumulative departure method, and wavelet analysis to examine drought patterns. Results indicate significant drying trends in the IRV beginning in 2005, with frequent drought events from 2015 onwards, and 2019 marking a key transition from wet to dry conditions. The overall drought rate was -0.09/10a, suggesting a milder drought severity in the IRV compared to broader Xinjiang. Seasonally, the IRV experiences drier summers and wetter winters relative to the region's averages, with negligible changes in autumn and milder drought conditions in spring. Abrupt changes in drying seasons occurred later than in Xinjiang, with delays of 5, 21, and over 37 years for spring, summer, and autumn, respectively, indicating a lagging response. Spatially, the western plains are more prone to aridification than the central and eastern mountainous regions. significant differences in drought cycles, longer than those in Xinjiang, with distinct wet-dry phases observed over multiple time scales and across seasons highlighting the complexity of drought variability in IRV. In conclusion, the Vally exhibits unique drought characteristics, with milder intensities, pronounced seasonal variation, spatial heterogeneity, and notable resilience to climate change. These findings emphasize the necessity of region-specific drought management strategies, as those effective on a larger regional scale may not be suitable for subregions.